- A critical attitude towards the use of data and the tools to analyse real world events- How empirical observations can be interpreted and evaluated from an economic point of view- Experience in working with modern statistical packages and tools

Description

People who retire earlier, die earlier. Would you conclude from this evidence that it is better not to retire early? This course offers you (1) tools with which you can take a critical look at such claims, (2) tools with which you can investigate data yourself. In case of this example, causality might run in the opposite direction: people who are healthier work longer than those who are less healthy. So deceasing earlier might not be caused by earlier retirement but be due to worse health of early retirees. To estimate whether early retirement really increases health risks we need a better research strategy.This course offers such methods and tools along with assignments to see how it works in practice. It consists of two parts: (i) basic tools and methods (ii) applying the methods to a data set by writing a short paper. The first part develops an understanding of the tools with which empirical claims can be established or refuted. The philosophy is to explain the empirical strategies in an intuitive way. We focus on analysing economic phenomena, such as labour market effects on health, wage and earnings equations, the Philips curve or money demand. In this part of the course, the group will be split up in two subgroups which will focus on specific topics in line with their field of study.